{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src='http://hilpisch.com/taim_logo.png' width=\"350px\" align=\"right\">"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Artificial Intelligence in Finance"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data-Driven Finance (a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Dr Yves J Hilpisch | The AI Machine\n",
    "\n",
    "http://aimachine.io | http://twitter.com/dyjh"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Financial Econometrics and Regression"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "def f(x):\n",
    "    return 2 + 1 / 2 * x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-4, -3, -2, -1,  0,  1,  2,  3,  4])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x = np.arange(-4, 5)\n",
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. ])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y = f(x)\n",
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-4, -3, -2, -1,  0,  1,  2,  3,  4])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0. , 0.5, 1. , 1.5, 2. , 2.5, 3. , 3.5, 4. ])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.49999999999999994"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "beta = np.cov(x, y, ddof=0)[0, 1] / x.var()\n",
    "beta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "alpha = y.mean() - beta * x.mean()\n",
    "alpha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "y_ = alpha + beta * x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(y_, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Availability"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to a (paid) subscribtion to the Eikon Data API (https://developers.refinitiv.com/eikon-apis/eikon-data-apis), the following code requires the `eikon` Python package:\n",
    "\n",
    "    pip install eikon"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "import eikon as ek\n",
    "import configparser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "c = configparser.ConfigParser()\n",
    "c.read('../aiif.cfg')\n",
    "ek.set_app_key(c['eikon']['app_id'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'1.1.6.post3'"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ek.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbols = ['AAPL.O', 'MSFT.O', 'NFLX.O', 'AMZN.O']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = ek.get_timeseries(symbols,\n",
    "                         fields='CLOSE',\n",
    "                         start_date='2019-07-01',\n",
    "                         end_date='2020-07-01')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 254 entries, 2019-07-01 to 2020-07-01\n",
      "Data columns (total 4 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   AAPL.O  254 non-null    float64\n",
      " 1   MSFT.O  254 non-null    float64\n",
      " 2   NFLX.O  254 non-null    float64\n",
      " 3   AMZN.O  254 non-null    float64\n",
      "dtypes: float64(4)\n",
      "memory usage: 9.9 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>CLOSE</th>\n",
       "      <th>AAPL.O</th>\n",
       "      <th>MSFT.O</th>\n",
       "      <th>NFLX.O</th>\n",
       "      <th>AMZN.O</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-06-25</th>\n",
       "      <td>91.2100</td>\n",
       "      <td>200.34</td>\n",
       "      <td>465.91</td>\n",
       "      <td>2754.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-26</th>\n",
       "      <td>88.4075</td>\n",
       "      <td>196.33</td>\n",
       "      <td>443.40</td>\n",
       "      <td>2692.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-29</th>\n",
       "      <td>90.4450</td>\n",
       "      <td>198.44</td>\n",
       "      <td>447.24</td>\n",
       "      <td>2680.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>91.2000</td>\n",
       "      <td>203.51</td>\n",
       "      <td>455.04</td>\n",
       "      <td>2758.82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-01</th>\n",
       "      <td>91.0275</td>\n",
       "      <td>204.70</td>\n",
       "      <td>485.64</td>\n",
       "      <td>2878.70</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "CLOSE        AAPL.O  MSFT.O  NFLX.O   AMZN.O\n",
       "Date                                        \n",
       "2020-06-25  91.2100  200.34  465.91  2754.58\n",
       "2020-06-26  88.4075  196.33  443.40  2692.87\n",
       "2020-06-29  90.4450  198.44  447.24  2680.38\n",
       "2020-06-30  91.2000  203.51  455.04  2758.82\n",
       "2020-07-01  91.0275  204.70  485.64  2878.70"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = ek.get_timeseries('AMZN.O',\n",
    "                         fields='*',\n",
    "                         start_date='2020-09-24',\n",
    "                         end_date='2020-09-25',\n",
    "                         interval='minute')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 899 entries, 2020-09-24 00:00:00 to 2020-09-25 00:00:00\n",
      "Data columns (total 6 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   HIGH    899 non-null    float64\n",
      " 1   LOW     899 non-null    float64\n",
      " 2   OPEN    899 non-null    float64\n",
      " 3   CLOSE   899 non-null    float64\n",
      " 4   COUNT   899 non-null    Int64  \n",
      " 5   VOLUME  899 non-null    Int64  \n",
      "dtypes: Int64(2), float64(4)\n",
      "memory usage: 50.9 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>AMZN.O</th>\n",
       "      <th>HIGH</th>\n",
       "      <th>LOW</th>\n",
       "      <th>OPEN</th>\n",
       "      <th>CLOSE</th>\n",
       "      <th>COUNT</th>\n",
       "      <th>VOLUME</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-09-24 00:00:00</th>\n",
       "      <td>2977.00</td>\n",
       "      <td>2971.21</td>\n",
       "      <td>2976.70</td>\n",
       "      <td>2972.87</td>\n",
       "      <td>35</td>\n",
       "      <td>154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-24 08:01:00</th>\n",
       "      <td>2991.18</td>\n",
       "      <td>2984.40</td>\n",
       "      <td>2984.40</td>\n",
       "      <td>2991.18</td>\n",
       "      <td>4</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-24 08:02:00</th>\n",
       "      <td>2991.07</td>\n",
       "      <td>2990.00</td>\n",
       "      <td>2991.07</td>\n",
       "      <td>2990.00</td>\n",
       "      <td>2</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-24 08:03:00</th>\n",
       "      <td>2990.01</td>\n",
       "      <td>2985.00</td>\n",
       "      <td>2990.00</td>\n",
       "      <td>2989.01</td>\n",
       "      <td>11</td>\n",
       "      <td>70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-24 08:04:00</th>\n",
       "      <td>2993.76</td>\n",
       "      <td>2990.00</td>\n",
       "      <td>2990.00</td>\n",
       "      <td>2993.76</td>\n",
       "      <td>3</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AMZN.O                  HIGH      LOW     OPEN    CLOSE  COUNT  VOLUME\n",
       "Date                                                                  \n",
       "2020-09-24 00:00:00  2977.00  2971.21  2976.70  2972.87     35     154\n",
       "2020-09-24 08:01:00  2991.18  2984.40  2984.40  2991.18      4      15\n",
       "2020-09-24 08:02:00  2991.07  2990.00  2991.07  2990.00      2       8\n",
       "2020-09-24 08:03:00  2990.01  2985.00  2990.00  2989.01     11      70\n",
       "2020-09-24 08:04:00  2993.76  2990.00  2990.00  2993.76      3       5"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_grid, err = ek.get_data(['AAPL.O', 'IBM', 'GOOG.O', 'AMZN.O'],\n",
    "                             ['TR.TotalReturnYTD', 'TR.WACCBeta',\n",
    "                              'YRHIGH', 'YRLOW',\n",
    "                              'TR.Ebitda', 'TR.GrossProfit'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Instrument</th>\n",
       "      <th>YTD Total Return</th>\n",
       "      <th>Beta</th>\n",
       "      <th>YRHIGH</th>\n",
       "      <th>YRLOW</th>\n",
       "      <th>EBITDA</th>\n",
       "      <th>Gross Profit</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>AAPL.O</td>\n",
       "      <td>54.000938</td>\n",
       "      <td>1.326924</td>\n",
       "      <td>137.9800</td>\n",
       "      <td>53.1525</td>\n",
       "      <td>76477000000</td>\n",
       "      <td>98392000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IBM</td>\n",
       "      <td>-7.929417</td>\n",
       "      <td>1.132158</td>\n",
       "      <td>158.7500</td>\n",
       "      <td>90.5600</td>\n",
       "      <td>18986000000</td>\n",
       "      <td>36488000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>GOOG.O</td>\n",
       "      <td>8.073178</td>\n",
       "      <td>1.114466</td>\n",
       "      <td>1733.1799</td>\n",
       "      <td>1013.5361</td>\n",
       "      <td>47579000000</td>\n",
       "      <td>89961000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AMZN.O</td>\n",
       "      <td>67.499892</td>\n",
       "      <td>1.356394</td>\n",
       "      <td>3552.2500</td>\n",
       "      <td>1626.0318</td>\n",
       "      <td>30256000000</td>\n",
       "      <td>114986000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Instrument  YTD Total Return      Beta     YRHIGH      YRLOW       EBITDA  \\\n",
       "0     AAPL.O         54.000938  1.326924   137.9800    53.1525  76477000000   \n",
       "1        IBM         -7.929417  1.132158   158.7500    90.5600  18986000000   \n",
       "2     GOOG.O          8.073178  1.114466  1733.1799  1013.5361  47579000000   \n",
       "3     AMZN.O         67.499892  1.356394  3552.2500  1626.0318  30256000000   \n",
       "\n",
       "   Gross Profit  \n",
       "0   98392000000  \n",
       "1   36488000000  \n",
       "2   89961000000  \n",
       "3  114986000000  "
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In addition to a (free paper trading) account with Oanda (http://oanda.com), the following code requires the `tpqoa` package:\n",
    "\n",
    "    pip install --upgrade git+https://github.com/yhilpisch/tpqoa.git"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tpqoa"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "oa = tpqoa.tpqoa('../aiif.cfg')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-09-28T14:35:25.907667721Z 10889.6 10925.6\n",
      "2020-09-28T14:35:32.298723799Z 10888.8 10924.8\n",
      "2020-09-28T14:35:33.881374203Z 10889.5 10925.5\n",
      "2020-09-28T14:35:34.340705377Z 10888.8 10924.8\n",
      "2020-09-28T14:35:35.510052309Z 10888.5 10924.5\n"
     ]
    }
   ],
   "source": [
    "oa.stream_data('BTC_USD', stop=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = ek.get_timeseries('AAPL.O',\n",
    "                         fields='*',\n",
    "                         start_date='2020-09-25 15:00:00',\n",
    "                         end_date='2020-09-25 15:15:00',\n",
    "                         interval='tick')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 34647 entries, 2020-09-25 15:00:00.006000 to 2020-09-25 15:14:59.996000\n",
      "Data columns (total 2 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   VALUE   34616 non-null  float64\n",
      " 1   VOLUME  34647 non-null  Int64  \n",
      "dtypes: Int64(1), float64(1)\n",
      "memory usage: 845.9 KB\n"
     ]
    }
   ],
   "source": [
    "data.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>AAPL.O</th>\n",
       "      <th>VALUE</th>\n",
       "      <th>VOLUME</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.006</th>\n",
       "      <td>110.09</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.006</th>\n",
       "      <td>NaN</td>\n",
       "      <td>911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.009</th>\n",
       "      <td>110.09</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.010</th>\n",
       "      <td>110.09</td>\n",
       "      <td>126</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.010</th>\n",
       "      <td>110.09</td>\n",
       "      <td>100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.010</th>\n",
       "      <td>110.09</td>\n",
       "      <td>74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.010</th>\n",
       "      <td>110.09</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-25 15:00:00.106</th>\n",
       "      <td>110.10</td>\n",
       "      <td>50</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "AAPL.O                    VALUE  VOLUME\n",
       "Date                                   \n",
       "2020-09-25 15:00:00.006  110.09     100\n",
       "2020-09-25 15:00:00.006     NaN     911\n",
       "2020-09-25 15:00:00.009  110.09     200\n",
       "2020-09-25 15:00:00.010  110.09     126\n",
       "2020-09-25 15:00:00.010  110.09     100\n",
       "2020-09-25 15:00:00.010  110.09      74\n",
       "2020-09-25 15:00:00.010  110.09     200\n",
       "2020-09-25 15:00:00.106  110.10      50"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head(8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "news = ek.get_news_headlines('R:TSLA.O PRODUCTION',\n",
    "                         date_from='2020-06-01',\n",
    "                         date_to='2020-08-01',\n",
    "                         count=7\n",
    "                        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>versionCreated</th>\n",
       "      <th>text</th>\n",
       "      <th>storyId</th>\n",
       "      <th>sourceCode</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-07-29 11:02:31.276</th>\n",
       "      <td>2020-07-29 11:02:31.276000+00:00</td>\n",
       "      <td>Tesla Launches Hiring Spree in China as It Pre...</td>\n",
       "      <td>urn:newsml:reuters.com:20200729:nCXG3W8s9X:1</td>\n",
       "      <td>NS:CAIXIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-28 00:59:48.000</th>\n",
       "      <td>2020-07-28 00:59:48+00:00</td>\n",
       "      <td>Tesla hiring in Shanghai as production ramps up</td>\n",
       "      <td>urn:newsml:reuters.com:20200728:nL3N2EY3PG:8</td>\n",
       "      <td>NS:RTRS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-23 21:20:36.090</th>\n",
       "      <td>2020-07-23 21:20:36.090000+00:00</td>\n",
       "      <td>Tesla speeds up Model 3 production in Shanghai</td>\n",
       "      <td>urn:newsml:reuters.com:20200723:nNRAcf1v8f:1</td>\n",
       "      <td>NS:SOUTHC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-23 08:22:17.000</th>\n",
       "      <td>2020-07-23 08:22:17+00:00</td>\n",
       "      <td>UPDATE 1-'Please mine more nickel,' Musk urges...</td>\n",
       "      <td>urn:newsml:reuters.com:20200723:nL3N2EU1P9:1</td>\n",
       "      <td>NS:RTRS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-23 07:08:48.000</th>\n",
       "      <td>2020-07-23 07:46:56+00:00</td>\n",
       "      <td>'Please mine more nickel,' Musk urges as Tesla...</td>\n",
       "      <td>urn:newsml:reuters.com:20200723:nL3N2EU0HH:1</td>\n",
       "      <td>NS:RTRS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-23 00:55:54.000</th>\n",
       "      <td>2020-07-23 00:55:54+00:00</td>\n",
       "      <td>USA-Tesla choisit le Texas pour la production ...</td>\n",
       "      <td>urn:newsml:reuters.com:20200723:nL5N2EU03M:1</td>\n",
       "      <td>NS:RTRS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-07-22 21:35:42.640</th>\n",
       "      <td>2020-07-22 22:13:26.597000+00:00</td>\n",
       "      <td>TESLA INC - THE REAL LIMITATION ON TESLA GROWT...</td>\n",
       "      <td>urn:newsml:reuters.com:20200722:nFWN2ET120:2</td>\n",
       "      <td>NS:RTRS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          versionCreated  \\\n",
       "2020-07-29 11:02:31.276 2020-07-29 11:02:31.276000+00:00   \n",
       "2020-07-28 00:59:48.000        2020-07-28 00:59:48+00:00   \n",
       "2020-07-23 21:20:36.090 2020-07-23 21:20:36.090000+00:00   \n",
       "2020-07-23 08:22:17.000        2020-07-23 08:22:17+00:00   \n",
       "2020-07-23 07:08:48.000        2020-07-23 07:46:56+00:00   \n",
       "2020-07-23 00:55:54.000        2020-07-23 00:55:54+00:00   \n",
       "2020-07-22 21:35:42.640 2020-07-22 22:13:26.597000+00:00   \n",
       "\n",
       "                                                                      text  \\\n",
       "2020-07-29 11:02:31.276  Tesla Launches Hiring Spree in China as It Pre...   \n",
       "2020-07-28 00:59:48.000    Tesla hiring in Shanghai as production ramps up   \n",
       "2020-07-23 21:20:36.090     Tesla speeds up Model 3 production in Shanghai   \n",
       "2020-07-23 08:22:17.000  UPDATE 1-'Please mine more nickel,' Musk urges...   \n",
       "2020-07-23 07:08:48.000  'Please mine more nickel,' Musk urges as Tesla...   \n",
       "2020-07-23 00:55:54.000  USA-Tesla choisit le Texas pour la production ...   \n",
       "2020-07-22 21:35:42.640  TESLA INC - THE REAL LIMITATION ON TESLA GROWT...   \n",
       "\n",
       "                                                              storyId  \\\n",
       "2020-07-29 11:02:31.276  urn:newsml:reuters.com:20200729:nCXG3W8s9X:1   \n",
       "2020-07-28 00:59:48.000  urn:newsml:reuters.com:20200728:nL3N2EY3PG:8   \n",
       "2020-07-23 21:20:36.090  urn:newsml:reuters.com:20200723:nNRAcf1v8f:1   \n",
       "2020-07-23 08:22:17.000  urn:newsml:reuters.com:20200723:nL3N2EU1P9:1   \n",
       "2020-07-23 07:08:48.000  urn:newsml:reuters.com:20200723:nL3N2EU0HH:1   \n",
       "2020-07-23 00:55:54.000  urn:newsml:reuters.com:20200723:nL5N2EU03M:1   \n",
       "2020-07-22 21:35:42.640  urn:newsml:reuters.com:20200722:nFWN2ET120:2   \n",
       "\n",
       "                        sourceCode  \n",
       "2020-07-29 11:02:31.276  NS:CAIXIN  \n",
       "2020-07-28 00:59:48.000    NS:RTRS  \n",
       "2020-07-23 21:20:36.090  NS:SOUTHC  \n",
       "2020-07-23 08:22:17.000    NS:RTRS  \n",
       "2020-07-23 07:08:48.000    NS:RTRS  \n",
       "2020-07-23 00:55:54.000    NS:RTRS  \n",
       "2020-07-22 21:35:42.640    NS:RTRS  "
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "news"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "storyId = news['storyId'][1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import HTML"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div class=\"storyContent\" lang=\"en\"><style type=\"text/css\">.storyContent * {border-color:inherit !important;outline-color:inherit !important;}</style><p class=\"tr-by\">By Yilei Sun and Brenda Goh</p><p class=\"tr-story-p1\"><span class=\"tr-dateline\">SHANGHAI, July 28 (Reuters)</span><span class=\"tr-dl-sep\"> - </span>Tesla Inc <a href=\"reuters://REALTIME/Verb=FullQuote/ric=TSLA.O\" data-type=\"ric\" data-ric=\"TSLA.O\" translate=\"no\" dir=\"ltr\">TSLA.O</a> has launched a hiring spree in Shanghai with plans to bring on designers at its China studio and about 1,000 factory workers, job posts show, as the U.S. electric vehicle maker ramps up production in the world's biggest auto market.</p><p>The posts on the Tesla human resources department's official WeChat account mark the first time the California-based automaker has looked to hire designers in China. Tesla said in January it planned to open a design and research centre in China to make \"Chinese-style\" cars. <span> (<a href=\"reuters://REALTIME/verb=NewsStory/ric=nL4N29L20D\" data-type=\"storyId\" data-story-id=\"nL4N29L20D\" translate=\"no\" dir=\"ltr\" class=\"tr-pnac\">Full Story</a>)</span></p><p>The posts did not reveal how many designers Tesla planned to hire.</p><p>The company also planned to hire 600 workers at stamping, bodywork, painting and assembly workshops in Shanghai, according to a separate job post by the Lingang local government. Another 150 workers were needed for quality checks, 200 for logistics work and 20 for security, it added.</p><p>Two sources familiar with the matter said the recruitment drive was partly for the preparation of Model Y sport-utility vehicles at the Shanghai plant. Tesla is building manufacturing facilities for Model Ys in Shanghai from next year.<span> (<a href=\"reuters://REALTIME/verb=NewsStory/ric=nL3N2ET3UB\" data-type=\"storyId\" data-story-id=\"nL3N2ET3UB\" translate=\"no\" dir=\"ltr\" class=\"tr-pnac\">Full Story</a>)</span></p><p>Tesla did not immediately respond to a request for comment.</p><p>The company delivered over 30,000 units in China in the past quarter, most of them locally made Model 3 sedans. </p><p>In March it advertised for solar and energy storage project managers in China, as it moves to expand its energy business into the country.<span> (<a href=\"reuters://REALTIME/verb=NewsStory/ric=nB9N28S025\" data-type=\"storyId\" data-story-id=\"nB9N28S025\" translate=\"no\" dir=\"ltr\" class=\"tr-pnac\">Full Story</a>)</span><span> (<a href=\"reuters://REALTIME/verb=NewsStory/ric=nL8N2AZ3KE\" data-type=\"storyId\" data-story-id=\"nL8N2AZ3KE\" translate=\"no\" dir=\"ltr\" class=\"tr-pnac\">Full Story</a>)</span></p><p><br/></p><p class=\"tr-signoff\"> (Reporting by Yilei Sun and Brenda Goh; Editing by Stephen Coates)</p><p class=\"tr-contactinfo\">(( <a href=\"mailto:Y.Sun@thomsonreuters.com\" data-type=\"email\" translate=\"no\">Y.Sun@thomsonreuters.com</a> ; +86 10 66271262; Reuters Messaging: <a class=\"tr-link tr-link-rm\" href=\"rm://y.sun.thomsonreuters.com@reuters.net\">y.sun.thomsonreuters.com@reuters.net</a> ))</p><p class=\"line-break\"><br/></p><p class=\"tr-copyright\">(c) Copyright Thomson Reuters 2020. Click For Restrictions - https://agency.reuters.com/en/copyright.html</p><p class=\"line-break\"><br/></p><p class=\"tr-slugline\">Keywords: TESLA-CHINA/ (PIX)</p></div>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HTML(ek.get_news_story(storyId))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import nlp\n",
    "import requests"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "sources = [\n",
    "    'https://nr.apple.com/dE0b1T5G3u',  # iPad Pro\n",
    "    'https://nr.apple.com/dE4c7T6g1K',  # MacBook Air\n",
    "    'https://nr.apple.com/dE4q4r8A2A',  # Mac Mini\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "html = [requests.get(url).text for url in sources]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = [nlp.clean_up_text(t) for t in html]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'new ipad pro with all-screen designis most advanced, powerful ipad ever - apple global nav open menu global nav close menu apple shopping bag + search apple.com cancel apple mac ipad iphone watch tv music support shopping bag + newsroom open menu close menu archive apple tv+ press apple newsroom needs your permission to enable desktop notifications when new articles are published press release october 30, 2018 new ipad pro with all-screen designis most advanced, powerful ipad ever 11-inch and 12.9-inch models feature liquid retina display, powerful a12x bionic chip and face id introducing the new ipad pro with all-screen design and next-generation performance. new york apple today introduced the new ipad pro with all-screen design and next-generation performance, marking the biggest change to ipad ever. the all-new design pushes 11-inch and 12.9-inch liquid retina displays to the edges of ipad pro and integrates face id to securely unlock ipad with just a glance.1 the a12x bionic chip w'"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data[0][0:1001]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "from twitter import Twitter, OAuth"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = Twitter(auth=OAuth(c['twitter']['access_token'],\n",
    "                       c['twitter']['access_secret_token'],\n",
    "                       c['twitter']['api_key'],\n",
    "                       c['twitter']['api_secret_key']),\n",
    "            retry=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = t.statuses.home_timeline(count=15)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RT @KenJee_DS: Interested in what projects should be in your portfolio? I think this video can help! Also, there is a bonus giveaway of 3 f…\n",
      "U.S. judge blocks Trump administration's TikTok download ban https://t.co/TGakzE3dMW\n",
      "SoftBank will bring Bear’s serving robots to Japan, amid restaurant labor shortages https://t.co/IVokXHX6VS by @bheater\n",
      "Malta to ask for return of shark tooth given to Prince George https://t.co/wbx4pD7e33 https://t.co/AAJqk2ZLSB\n",
      "Here's how the first presidential debate is adapting to Covid-19 https://t.co/0bTTIS5yRC\n",
      "#DataAISummit Europe will gather more than 20,000 data professionals to share and network over open-source technolo… https://t.co/RHAIf3bBgy\n",
      "Börsenstart für #Siemens Energy: Nach einigem Auf und Ab hat sich der Börsengang für die meisten Aktionäre wohl gel… https://t.co/IfkU1w6KCG\n",
      "In recognition of Yom Kippur, I am honored to pay my respects at the Thessaloniki Jewish Museum, which commemorates… https://t.co/WhGVeqSYAe\n",
      "If you need a break from screaming into your pillow, join me at @WSJ's Women In The Workplace Forum on Sept 30! I’l… https://t.co/J8N1Mu70WW\n",
      "https://t.co/mTDGuhfdmZ\n",
      "I’m full of questions.\n",
      "https://t.co/jrP2HwAiu3\n",
      "Joe Biden just announced that he will not agree to a Drug Test. Gee, I wonder why?\n",
      "RT @thomasjbevan1: In retrospect every failure in my life came from not keeping the momentum going when I had it.\n",
      "\n",
      "And the successes came f…\n",
      "What is your plan surrounding temporary work visas for the United States in relation to #humantrafficking… https://t.co/9G7z3K0Auw\n"
     ]
    }
   ],
   "source": [
    "for e in l:\n",
    "    print(e['text'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = t.statuses.user_timeline(screen_name='dyjh', count=5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Investors wonder if the 60/40 portfolio has a future #assetmanagement https://t.co/Inf4LgXxXA via @financialtimes\n",
      "\"18 Revelations From a Trove of Trump Tax Records\" via @NYTimes https://t.co/yAG8AFBqvz\n",
      "Trump’s Taxes Show Chronic Losses and Years of Income Tax Avoidance https://t.co/rwxdRVAino\n",
      "SocGen’s maths geeks built an empire: do the sums still add up? https://t.co/8kzH3W4Y80 via @financialtimes\n",
      "GitHub to replace 'master' with 'main' starting next month #github https://t.co/miXJvaNHFD\n"
     ]
    }
   ],
   "source": [
    "for e in l:\n",
    "    print(e['text'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "d = t.search.tweets(q='#Python', count=7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RT @gp_pulipaka: Correlation Coefficients in #DataScience and #MachineLearning (in One Picture). #BigData #Analytics #AI #IoT #IIoT #Python…\n",
      "RT @SourabhSKatoch: Who else relates to this Instance? 😂\n",
      "\n",
      "#100DaysOfCode #Machinelearning #IoT #100DaysOfMLCode #Python #javascript #Nodejs…\n",
      "RT @gp_pulipaka: Correlation Coefficients in #DataScience and #MachineLearning (in One Picture). #BigData #Analytics #AI #IoT #IIoT #Python…\n",
      "RT @mdrashedul77: Check out my Gig on Fiverr:  https://t.co/Wy694JJGua \n",
      "#proggeek #code #python #javascript #Java #programming #Nodejs #ent…\n",
      "RT @gp_pulipaka: Correlation Coefficients in #DataScience and #MachineLearning (in One Picture). #BigData #Analytics #AI #IoT #IIoT #Python…\n",
      "RT @mdrashedul77: Check out my Gig on Fiverr:  https://t.co/Wy694JJGua \n",
      "#proggeek #code #python #javascript #Java #programming #Nodejs #ent…\n",
      "RT @FreeHipwee: The WpFASTER WordPress Speed Optimization Master Course #udemyfree #udemycoupon \n",
      "\n",
      "=&gt; https://t.co/86EeT2n3ST\n",
      "\n",
      "#webdevelopme…\n"
     ]
    }
   ],
   "source": [
    "for e in d['statuses']:\n",
    "    print(e['text'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "l = t.statuses.user_timeline(screen_name='elonmusk', count=50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "tl = [e['text'] for e in l]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['@teslavibes That’s total market, not all Tesla. We do see Tesla reaching 20M vehicles/year probably before 2030, bu… https://t.co/GXnszaCAR3',\n",
       " '@CashMoneyLemon @CathieDWood @skorusARK Total market',\n",
       " '@CathieDWood @skorusARK Seven years for sure to 30M+ new fully electric vehicles per year, six years maybe. Five ye… https://t.co/FY4nwWbx56',\n",
       " '@flcnhvy @CathieDWood Both will do original cars',\n",
       " '@CathieDWood We aren’t cutting the price of Model 3 to $25k. I was referring to a future car that will be smaller than Model 3.']"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tl[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x720 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "wc = nlp.generate_word_cloud(' '.join(tl), 35)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Normative Theories Revisited"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean-Variance Portfolio Theory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "from pylab import plt, mpl\n",
    "from scipy.optimize import minimize\n",
    "plt.style.use('seaborn')\n",
    "mpl.rcParams['savefig.dpi'] = 300\n",
    "mpl.rcParams['font.family'] = 'serif'\n",
    "np.set_printoptions(precision=5, suppress=True,\n",
    "                   formatter={'float': lambda x: f'{x:6.3f}'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "url = 'http://hilpisch.com/aiif_eikon_eod_data.csv'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "raw = pd.read_csv(url, index_col=0, parse_dates=True).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 2516 entries, 2010-01-04 to 2019-12-31\n",
      "Data columns (total 12 columns):\n",
      " #   Column  Non-Null Count  Dtype  \n",
      "---  ------  --------------  -----  \n",
      " 0   AAPL.O  2516 non-null   float64\n",
      " 1   MSFT.O  2516 non-null   float64\n",
      " 2   INTC.O  2516 non-null   float64\n",
      " 3   AMZN.O  2516 non-null   float64\n",
      " 4   GS.N    2516 non-null   float64\n",
      " 5   SPY     2516 non-null   float64\n",
      " 6   .SPX    2516 non-null   float64\n",
      " 7   .VIX    2516 non-null   float64\n",
      " 8   EUR=    2516 non-null   float64\n",
      " 9   XAU=    2516 non-null   float64\n",
      " 10  GDX     2516 non-null   float64\n",
      " 11  GLD     2516 non-null   float64\n",
      "dtypes: float64(12)\n",
      "memory usage: 255.5 KB\n"
     ]
    }
   ],
   "source": [
    "raw.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "symbols = ['AAPL.O', 'MSFT.O', 'INTC.O', 'AMZN.O', 'GLD']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets = np.log(raw[symbols] / raw[symbols].shift(1)).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(raw[symbols[:]] / raw[symbols[:]].iloc[0]).plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0.2, 0.2, 0.2, 0.2, 0.2]"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "weights = len(rets.columns) * [1 / len(rets.columns)]\n",
    "weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "def port_return(rets, weights):\n",
    "    return np.dot(rets.mean(), weights) * 252  # annualized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.15694764653018106"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port_return(rets, weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "def port_volatility(rets, weights):\n",
    "    return np.dot(weights, np.dot(rets.cov() * 252 , weights)) ** 0.5  # annualized"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.16106507848480675"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port_volatility(rets, weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "def port_sharpe(rets, weights):\n",
    "    return port_return(rets, weights) / port_volatility(rets, weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.97443622172255"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "port_sharpe(rets, weights)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "w = np.random.random((1000, len(symbols)))\n",
    "w = (w.T / w.sum(axis=1)).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0.304,  0.055,  0.136,  0.299,  0.206],\n",
       "       [ 0.299,  0.234,  0.240,  0.173,  0.055],\n",
       "       [ 0.156,  0.160,  0.228,  0.231,  0.226],\n",
       "       [ 0.443,  0.231,  0.002,  0.029,  0.295],\n",
       "       [ 0.350,  0.118,  0.170,  0.317,  0.044]])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.000,  1.000,  1.000,  1.000,  1.000])"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "w[:5].sum(axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "pvr = [(port_volatility(rets[symbols], weights),\n",
    "        port_return(rets[symbols], weights))\n",
    "       for weights in w]\n",
    "pvr = np.array(pvr)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [],
   "source": [
    "psr = pvr[:, 1] / pvr[:, 0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 6))\n",
    "fig = plt.scatter(pvr[:, 0], pvr[:, 1],\n",
    "                  c=psr, cmap='coolwarm')\n",
    "cb = plt.colorbar(fig)\n",
    "cb.set_label('Sharpe ratio')\n",
    "plt.xlabel('expected volatility')\n",
    "plt.ylabel('expected return')\n",
    "plt.title(' | '.join(symbols));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 1), (0, 1), (0, 1), (0, 1), (0, 1)]"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bnds = len(symbols) * [(0, 1),]\n",
    "bnds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "cons = {'type': 'eq', 'fun': lambda weights: weights.sum() - 1}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [],
   "source": [
    "opt_weights = {}\n",
    "for year in range(2010, 2019):\n",
    "    rets_ = rets[symbols].loc[f'{year}-01-01':f'{year}-12-31']\n",
    "    ow = minimize(lambda weights: -port_sharpe(rets_, weights),\n",
    "                  len(symbols) * [1 / len(symbols)],\n",
    "                  bounds=bnds,\n",
    "                  constraints=cons)['x']\n",
    "    opt_weights[year] = ow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{2010: array([ 0.366,  0.000,  0.000,  0.056,  0.578]),\n",
       " 2011: array([ 0.543,  0.000,  0.077,  0.000,  0.380]),\n",
       " 2012: array([ 0.324,  0.000,  0.000,  0.471,  0.205]),\n",
       " 2013: array([ 0.012,  0.305,  0.219,  0.464,  0.000]),\n",
       " 2014: array([ 0.452,  0.115,  0.419,  0.000,  0.015]),\n",
       " 2015: array([ 0.000,  0.000,  0.000,  1.000,  0.000]),\n",
       " 2016: array([ 0.150,  0.260,  0.000,  0.058,  0.533]),\n",
       " 2017: array([ 0.231,  0.203,  0.031,  0.109,  0.426]),\n",
       " 2018: array([ 0.000,  0.295,  0.000,  0.705,  0.000])}"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "opt_weights"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = pd.DataFrame()\n",
    "for year in range(2010, 2019):\n",
    "    rets_ = rets[symbols].loc[f'{year}-01-01':f'{year}-12-31']\n",
    "    epv = port_volatility(rets_, opt_weights[year])\n",
    "    epr = port_return(rets_, opt_weights[year])\n",
    "    esr = epr / epv\n",
    "    rets_ = rets[symbols].loc[f'{year + 1}-01-01':f'{year + 1}-12-31']\n",
    "    rpv = port_volatility(rets_, opt_weights[year])\n",
    "    rpr = port_return(rets_, opt_weights[year])\n",
    "    rsr = rpr / rpv\n",
    "    res = res.append(pd.DataFrame({'epv': epv, 'epr': epr, 'esr': esr,\n",
    "                                   'rpv': rpv, 'rpr': rpr, 'rsr': rsr},\n",
    "                                  index=[year + 1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epv</th>\n",
       "      <th>epr</th>\n",
       "      <th>esr</th>\n",
       "      <th>rpv</th>\n",
       "      <th>rpr</th>\n",
       "      <th>rsr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011</th>\n",
       "      <td>0.157440</td>\n",
       "      <td>0.303003</td>\n",
       "      <td>1.924564</td>\n",
       "      <td>0.160622</td>\n",
       "      <td>0.133836</td>\n",
       "      <td>0.833235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012</th>\n",
       "      <td>0.173279</td>\n",
       "      <td>0.169321</td>\n",
       "      <td>0.977156</td>\n",
       "      <td>0.182292</td>\n",
       "      <td>0.161375</td>\n",
       "      <td>0.885256</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013</th>\n",
       "      <td>0.202460</td>\n",
       "      <td>0.278459</td>\n",
       "      <td>1.375378</td>\n",
       "      <td>0.168714</td>\n",
       "      <td>0.166897</td>\n",
       "      <td>0.989228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014</th>\n",
       "      <td>0.181544</td>\n",
       "      <td>0.368961</td>\n",
       "      <td>2.032353</td>\n",
       "      <td>0.197798</td>\n",
       "      <td>0.026830</td>\n",
       "      <td>0.135645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015</th>\n",
       "      <td>0.160340</td>\n",
       "      <td>0.309486</td>\n",
       "      <td>1.930190</td>\n",
       "      <td>0.211368</td>\n",
       "      <td>-0.024560</td>\n",
       "      <td>-0.116194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016</th>\n",
       "      <td>0.326730</td>\n",
       "      <td>0.778330</td>\n",
       "      <td>2.382179</td>\n",
       "      <td>0.296565</td>\n",
       "      <td>0.103870</td>\n",
       "      <td>0.350242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017</th>\n",
       "      <td>0.106148</td>\n",
       "      <td>0.090933</td>\n",
       "      <td>0.856663</td>\n",
       "      <td>0.079521</td>\n",
       "      <td>0.230630</td>\n",
       "      <td>2.900235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018</th>\n",
       "      <td>0.086548</td>\n",
       "      <td>0.260702</td>\n",
       "      <td>3.012226</td>\n",
       "      <td>0.157337</td>\n",
       "      <td>0.038234</td>\n",
       "      <td>0.243004</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019</th>\n",
       "      <td>0.323796</td>\n",
       "      <td>0.228008</td>\n",
       "      <td>0.704174</td>\n",
       "      <td>0.207672</td>\n",
       "      <td>0.275819</td>\n",
       "      <td>1.328147</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           epv       epr       esr       rpv       rpr       rsr\n",
       "2011  0.157440  0.303003  1.924564  0.160622  0.133836  0.833235\n",
       "2012  0.173279  0.169321  0.977156  0.182292  0.161375  0.885256\n",
       "2013  0.202460  0.278459  1.375378  0.168714  0.166897  0.989228\n",
       "2014  0.181544  0.368961  2.032353  0.197798  0.026830  0.135645\n",
       "2015  0.160340  0.309486  1.930190  0.211368 -0.024560 -0.116194\n",
       "2016  0.326730  0.778330  2.382179  0.296565  0.103870  0.350242\n",
       "2017  0.106148  0.090933  0.856663  0.079521  0.230630  2.900235\n",
       "2018  0.086548  0.260702  3.012226  0.157337  0.038234  0.243004\n",
       "2019  0.323796  0.228008  0.704174  0.207672  0.275819  1.328147"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "epv    0.190920\n",
       "epr    0.309689\n",
       "esr    1.688320\n",
       "rpv    0.184654\n",
       "rpr    0.123659\n",
       "rsr    0.838755\n",
       "dtype: float64"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res.mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
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       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epv</th>\n",
       "      <th>rpv</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>epv</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.765733</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rpv</th>\n",
       "      <td>0.765733</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          epv       rpv\n",
       "epv  1.000000  0.765733\n",
       "rpv  0.765733  1.000000"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[['epv', 'rpv']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[['epv', 'rpv']].plot(kind='bar', figsize=(10, 6),\n",
    "        title='Expected vs. Realized Portfolio Volatility');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>epr</th>\n",
       "      <th>rpr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>epr</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.350437</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rpr</th>\n",
       "      <td>-0.350437</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          epr       rpr\n",
       "epr  1.000000 -0.350437\n",
       "rpr -0.350437  1.000000"
      ]
     },
     "execution_count": 80,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[['epr', 'rpr']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[['epr', 'rpr']].plot(kind='bar', figsize=(10, 6),\n",
    "        title='Expected vs. Realized Portfolio Return');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>esr</th>\n",
       "      <th>rsr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>esr</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.698607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rsr</th>\n",
       "      <td>-0.698607</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          esr       rsr\n",
       "esr  1.000000 -0.698607\n",
       "rsr -0.698607  1.000000"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[['esr', 'rsr']].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[['esr', 'rsr']].plot(kind='bar', figsize=(10, 6),\n",
    "        title='Expected vs. Realized Sharpe Ratio');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Capital Asset Pricing Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [],
   "source": [
    "r = 0.005"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [],
   "source": [
    "market = '.SPX'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets = np.log(raw / raw.shift(1)).dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "AAPL.O\n",
      "======================================================\n",
      "2011 | beta: 1.052 | mu_capm: -0.000 | mu_real:  0.228\n",
      "2012 | beta: 0.764 | mu_capm:  0.098 | mu_real:  0.275\n",
      "2013 | beta: 1.266 | mu_capm:  0.327 | mu_real:  0.053\n",
      "2014 | beta: 0.630 | mu_capm:  0.070 | mu_real:  0.320\n",
      "2015 | beta: 0.833 | mu_capm: -0.005 | mu_real: -0.047\n",
      "2016 | beta: 1.144 | mu_capm:  0.103 | mu_real:  0.096\n",
      "2017 | beta: 1.009 | mu_capm:  0.180 | mu_real:  0.381\n",
      "2018 | beta: 1.379 | mu_capm: -0.091 | mu_real: -0.071\n",
      "2019 | beta: 1.252 | mu_capm:  0.316 | mu_real:  0.621\n",
      "\n",
      "MSFT.O\n",
      "======================================================\n",
      "2011 | beta: 0.890 | mu_capm:  0.001 | mu_real: -0.072\n",
      "2012 | beta: 0.816 | mu_capm:  0.104 | mu_real:  0.029\n",
      "2013 | beta: 1.109 | mu_capm:  0.287 | mu_real:  0.337\n",
      "2014 | beta: 0.876 | mu_capm:  0.095 | mu_real:  0.216\n",
      "2015 | beta: 0.955 | mu_capm: -0.007 | mu_real:  0.178\n",
      "2016 | beta: 1.249 | mu_capm:  0.113 | mu_real:  0.113\n",
      "2017 | beta: 1.224 | mu_capm:  0.217 | mu_real:  0.321\n",
      "2018 | beta: 1.303 | mu_capm: -0.086 | mu_real:  0.172\n",
      "2019 | beta: 1.442 | mu_capm:  0.364 | mu_real:  0.440\n",
      "\n",
      "INTC.O\n",
      "======================================================\n",
      "2011 | beta: 1.081 | mu_capm: -0.000 | mu_real:  0.142\n",
      "2012 | beta: 0.842 | mu_capm:  0.108 | mu_real: -0.163\n",
      "2013 | beta: 1.081 | mu_capm:  0.280 | mu_real:  0.230\n",
      "2014 | beta: 0.883 | mu_capm:  0.096 | mu_real:  0.335\n",
      "2015 | beta: 1.055 | mu_capm: -0.008 | mu_real: -0.052\n",
      "2016 | beta: 1.009 | mu_capm:  0.092 | mu_real:  0.051\n",
      "2017 | beta: 1.261 | mu_capm:  0.223 | mu_real:  0.242\n",
      "2018 | beta: 1.163 | mu_capm: -0.076 | mu_real:  0.017\n",
      "2019 | beta: 1.376 | mu_capm:  0.347 | mu_real:  0.243\n",
      "\n",
      "AMZN.O\n",
      "======================================================\n",
      "2011 | beta: 1.102 | mu_capm: -0.001 | mu_real: -0.039\n",
      "2012 | beta: 0.958 | mu_capm:  0.122 | mu_real:  0.374\n",
      "2013 | beta: 1.116 | mu_capm:  0.289 | mu_real:  0.464\n",
      "2014 | beta: 1.262 | mu_capm:  0.135 | mu_real: -0.251\n",
      "2015 | beta: 1.473 | mu_capm: -0.013 | mu_real:  0.778\n",
      "2016 | beta: 1.122 | mu_capm:  0.102 | mu_real:  0.104\n",
      "2017 | beta: 1.118 | mu_capm:  0.199 | mu_real:  0.446\n",
      "2018 | beta: 1.300 | mu_capm: -0.086 | mu_real:  0.251\n",
      "2019 | beta: 1.619 | mu_capm:  0.408 | mu_real:  0.207\n"
     ]
    }
   ],
   "source": [
    "for sym in rets.columns[:4]:\n",
    "    print('\\n' + sym)\n",
    "    print(54 * '=')\n",
    "    for year in range(2010, 2019):\n",
    "        rets_ = rets.loc[f'{year}-01-01':f'{year}-12-31']\n",
    "        muM = rets_[market].mean() * 252\n",
    "        cov = rets_.cov().loc[sym, market]\n",
    "        var = rets_[market].var()\n",
    "        beta = cov / var\n",
    "        rets_ = rets.loc[f'{year + 1}-01-01':f'{year + 1}-12-31']\n",
    "        muM = rets_[market].mean() * 252\n",
    "        mu_capm = r + beta * (muM - r)\n",
    "        mu_real = rets_[sym].mean() * 252\n",
    "        res = res.append(pd.DataFrame({'symbol': sym,\n",
    "                                       'mu_capm': mu_capm,\n",
    "                                       'mu_real': mu_real},\n",
    "                                      index=[year + 1]),\n",
    "                        sort=True)\n",
    "        print('{} | beta: {:.3f} | mu_capm: {:6.3f} | mu_real: {:6.3f}'\n",
    "              .format(year + 1, beta, mu_capm, mu_real))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [],
   "source": [
    "sym = 'AMZN.O'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mu_capm</th>\n",
       "      <th>mu_real</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mu_capm</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.004826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mu_real</th>\n",
       "      <td>-0.004826</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          mu_capm   mu_real\n",
       "mu_capm  1.000000 -0.004826\n",
       "mu_real -0.004826  1.000000"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[res['symbol'] == sym].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[res['symbol'] == sym].plot(kind='bar',\n",
    "                figsize=(10, 6), title=sym);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mu_capm</th>\n",
       "      <th>mu_real</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL.O</th>\n",
       "      <td>0.110855</td>\n",
       "      <td>0.206158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN.O</th>\n",
       "      <td>0.128223</td>\n",
       "      <td>0.259395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INTC.O</th>\n",
       "      <td>0.117929</td>\n",
       "      <td>0.116180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT.O</th>\n",
       "      <td>0.120844</td>\n",
       "      <td>0.192655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         mu_capm   mu_real\n",
       "symbol                    \n",
       "AAPL.O  0.110855  0.206158\n",
       "AMZN.O  0.128223  0.259395\n",
       "INTC.O  0.117929  0.116180\n",
       "MSFT.O  0.120844  0.192655"
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = res.groupby('symbol').mean()\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped.plot(kind='bar', figsize=(10, 6), title='Average Values');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Arbitrage-Pricing Theory"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "factors = ['.SPX', '.VIX', 'EUR=', 'XAU=']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.set_printoptions(formatter={'float': lambda x: f'{x:5.2f}'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "AAPL.O\n",
      "=======================================================================\n",
      "2011 | fl: [ 0.91 -0.04 -0.35  0.12] | mu_apt:  0.011 | mu_real:  0.228\n",
      "2012 | fl: [ 0.76 -0.02 -0.24  0.05] | mu_apt:  0.099 | mu_real:  0.275\n",
      "2013 | fl: [ 1.67  0.04 -0.56  0.10] | mu_apt:  0.366 | mu_real:  0.053\n",
      "2014 | fl: [ 0.53 -0.00  0.02  0.16] | mu_apt:  0.050 | mu_real:  0.320\n",
      "2015 | fl: [ 1.07  0.02  0.25  0.01] | mu_apt: -0.038 | mu_real: -0.047\n",
      "2016 | fl: [ 1.21  0.01 -0.14 -0.02] | mu_apt:  0.110 | mu_real:  0.096\n",
      "2017 | fl: [ 1.10  0.01 -0.15 -0.02] | mu_apt:  0.170 | mu_real:  0.381\n",
      "2018 | fl: [ 1.06 -0.03 -0.15  0.12] | mu_apt: -0.088 | mu_real: -0.071\n",
      "2019 | fl: [ 1.37  0.01 -0.20  0.13] | mu_apt:  0.364 | mu_real:  0.621\n",
      "\n",
      "MSFT.O\n",
      "=======================================================================\n",
      "2011 | fl: [ 0.98  0.01  0.02 -0.11] | mu_apt: -0.008 | mu_real: -0.072\n",
      "2012 | fl: [ 0.82  0.00 -0.03 -0.01] | mu_apt:  0.103 | mu_real:  0.029\n",
      "2013 | fl: [ 1.14  0.00 -0.07 -0.01] | mu_apt:  0.294 | mu_real:  0.337\n",
      "2014 | fl: [ 1.28  0.05  0.04  0.07] | mu_apt:  0.149 | mu_real:  0.216\n",
      "2015 | fl: [ 1.20  0.03  0.05  0.01] | mu_apt: -0.016 | mu_real:  0.178\n",
      "2016 | fl: [ 1.44  0.03 -0.17 -0.02] | mu_apt:  0.127 | mu_real:  0.113\n",
      "2017 | fl: [ 1.33  0.01 -0.14  0.00] | mu_apt:  0.216 | mu_real:  0.321\n",
      "2018 | fl: [ 1.10 -0.02 -0.14  0.22] | mu_apt: -0.087 | mu_real:  0.172\n",
      "2019 | fl: [ 1.51  0.01 -0.16 -0.02] | mu_apt:  0.378 | mu_real:  0.440\n",
      "\n",
      "INTC.O\n",
      "=======================================================================\n",
      "2011 | fl: [ 1.17  0.01  0.05 -0.13] | mu_apt: -0.010 | mu_real:  0.142\n",
      "2012 | fl: [ 1.03  0.04  0.01  0.03] | mu_apt:  0.122 | mu_real: -0.163\n",
      "2013 | fl: [ 1.06 -0.01 -0.10  0.01] | mu_apt:  0.267 | mu_real:  0.230\n",
      "2014 | fl: [ 0.96  0.02  0.36 -0.02] | mu_apt:  0.063 | mu_real:  0.335\n",
      "2015 | fl: [ 0.93 -0.01 -0.09  0.02] | mu_apt:  0.001 | mu_real: -0.052\n",
      "2016 | fl: [ 1.02  0.00 -0.05  0.06] | mu_apt:  0.099 | mu_real:  0.051\n",
      "2017 | fl: [ 1.41  0.02 -0.18  0.03] | mu_apt:  0.226 | mu_real:  0.242\n",
      "2018 | fl: [ 1.12 -0.01 -0.11  0.17] | mu_apt: -0.076 | mu_real:  0.017\n",
      "2019 | fl: [ 1.50  0.01 -0.34  0.30] | mu_apt:  0.431 | mu_real:  0.243\n",
      "\n",
      "AMZN.O\n",
      "=======================================================================\n",
      "2011 | fl: [ 1.02 -0.03 -0.18 -0.14] | mu_apt: -0.016 | mu_real: -0.039\n",
      "2012 | fl: [ 0.98 -0.01 -0.17 -0.09] | mu_apt:  0.117 | mu_real:  0.374\n",
      "2013 | fl: [ 1.07 -0.00  0.09  0.00] | mu_apt:  0.282 | mu_real:  0.464\n",
      "2014 | fl: [ 1.54  0.03  0.01 -0.08] | mu_apt:  0.176 | mu_real: -0.251\n",
      "2015 | fl: [ 1.26 -0.02  0.45 -0.11] | mu_apt: -0.044 | mu_real:  0.778\n",
      "2016 | fl: [ 1.06 -0.00 -0.15 -0.04] | mu_apt:  0.099 | mu_real:  0.104\n",
      "2017 | fl: [ 0.94 -0.02  0.12 -0.03] | mu_apt:  0.185 | mu_real:  0.446\n",
      "2018 | fl: [ 0.90 -0.04 -0.25  0.28] | mu_apt: -0.085 | mu_real:  0.251\n",
      "2019 | fl: [ 1.99  0.05 -0.37  0.12] | mu_apt:  0.506 | mu_real:  0.207\n"
     ]
    }
   ],
   "source": [
    "for sym in rets.columns[:4]:\n",
    "    print('\\n' + sym)\n",
    "    print(71 * '=')\n",
    "    for year in range(2010, 2019):\n",
    "        rets_ = rets.loc[f'{year}-01-01':f'{year}-12-31']\n",
    "        reg = np.linalg.lstsq(rets_[factors],\n",
    "                              rets_[sym], rcond=-1)[0]\n",
    "        rets_ = rets.loc[f'{year + 1}-01-01':f'{year + 1}-12-31']\n",
    "        mu_apt = np.dot(rets_[factors].mean() * 252, reg)\n",
    "        mu_real =  rets_[sym].mean() * 252\n",
    "        res = res.append(pd.DataFrame({'symbol': sym,\n",
    "                        'mu_apt': mu_apt, 'mu_real': mu_real},\n",
    "                         index=[year + 1]))\n",
    "        print('{} | fl: {} | mu_apt: {:6.3f} | mu_real: {:6.3f}'\n",
    "              .format(year + 1, reg.round(2), mu_apt, mu_real))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [],
   "source": [
    "sym = 'AMZN.O'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mu_apt</th>\n",
       "      <th>mu_real</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>mu_apt</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>-0.098281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mu_real</th>\n",
       "      <td>-0.098281</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           mu_apt   mu_real\n",
       "mu_apt   1.000000 -0.098281\n",
       "mu_real -0.098281  1.000000"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "res[res['symbol'] == sym].corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res[res['symbol'] == sym].plot(kind='bar',\n",
    "                figsize=(10, 6), title=sym);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mu_apt</th>\n",
       "      <th>mu_real</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AAPL.O</th>\n",
       "      <td>0.116116</td>\n",
       "      <td>0.206158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN.O</th>\n",
       "      <td>0.135528</td>\n",
       "      <td>0.259395</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INTC.O</th>\n",
       "      <td>0.124811</td>\n",
       "      <td>0.116180</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MSFT.O</th>\n",
       "      <td>0.128441</td>\n",
       "      <td>0.192655</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          mu_apt   mu_real\n",
       "symbol                    \n",
       "AAPL.O  0.116116  0.206158\n",
       "AMZN.O  0.135528  0.259395\n",
       "INTC.O  0.124811  0.116180\n",
       "MSFT.O  0.128441  0.192655"
      ]
     },
     "execution_count": 101,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped = res.groupby('symbol').mean()\n",
    "grouped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "grouped.plot(kind='bar', figsize=(10, 6), title='Average Values');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "factors = pd.read_csv('http://hilpisch.com/aiif_eikon_eod_factors.csv',\n",
    "                      index_col=0, parse_dates=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DatetimeIndex: 783 entries, 2017-01-02 to 2020-01-01\n",
      "Data columns (total 7 columns):\n",
      " #   Column      Non-Null Count  Dtype  \n",
      "---  ------      --------------  -----  \n",
      " 0   market      783 non-null    float64\n",
      " 1   size        783 non-null    float64\n",
      " 2   volatility  783 non-null    float64\n",
      " 3   value       783 non-null    float64\n",
      " 4   risk        783 non-null    float64\n",
      " 5   growth      783 non-null    float64\n",
      " 6   momentum    783 non-null    float64\n",
      "dtypes: float64(7)\n",
      "memory usage: 48.9 KB\n"
     ]
    }
   ],
   "source": [
    "factors.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "(factors / factors.iloc[0]).plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [],
   "source": [
    "start = '2017-01-01'\n",
    "end = '2020-01-01'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "retsd = rets.loc[start:end].copy()\n",
    "retsd.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "retsf = np.log(factors / factors.shift(1))\n",
    "retsf = retsf.loc[start:end]\n",
    "retsf.dropna(inplace=True)\n",
    "retsf = retsf.loc[retsd.index].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>market</th>\n",
       "      <th>size</th>\n",
       "      <th>volatility</th>\n",
       "      <th>value</th>\n",
       "      <th>risk</th>\n",
       "      <th>growth</th>\n",
       "      <th>momentum</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>market</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.935867</td>\n",
       "      <td>0.845010</td>\n",
       "      <td>0.964124</td>\n",
       "      <td>0.947150</td>\n",
       "      <td>0.959038</td>\n",
       "      <td>0.928705</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>size</th>\n",
       "      <td>0.935867</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.791767</td>\n",
       "      <td>0.965739</td>\n",
       "      <td>0.983238</td>\n",
       "      <td>0.835477</td>\n",
       "      <td>0.796420</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>volatility</th>\n",
       "      <td>0.845010</td>\n",
       "      <td>0.791767</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.778294</td>\n",
       "      <td>0.865467</td>\n",
       "      <td>0.818280</td>\n",
       "      <td>0.819585</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>value</th>\n",
       "      <td>0.964124</td>\n",
       "      <td>0.965739</td>\n",
       "      <td>0.778294</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.958359</td>\n",
       "      <td>0.864222</td>\n",
       "      <td>0.818796</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>risk</th>\n",
       "      <td>0.947150</td>\n",
       "      <td>0.983238</td>\n",
       "      <td>0.865467</td>\n",
       "      <td>0.958359</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.858546</td>\n",
       "      <td>0.825563</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>growth</th>\n",
       "      <td>0.959038</td>\n",
       "      <td>0.835477</td>\n",
       "      <td>0.818280</td>\n",
       "      <td>0.864222</td>\n",
       "      <td>0.858546</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.952956</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>momentum</th>\n",
       "      <td>0.928705</td>\n",
       "      <td>0.796420</td>\n",
       "      <td>0.819585</td>\n",
       "      <td>0.818796</td>\n",
       "      <td>0.825563</td>\n",
       "      <td>0.952956</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              market      size  volatility     value      risk    growth  \\\n",
       "market      1.000000  0.935867    0.845010  0.964124  0.947150  0.959038   \n",
       "size        0.935867  1.000000    0.791767  0.965739  0.983238  0.835477   \n",
       "volatility  0.845010  0.791767    1.000000  0.778294  0.865467  0.818280   \n",
       "value       0.964124  0.965739    0.778294  1.000000  0.958359  0.864222   \n",
       "risk        0.947150  0.983238    0.865467  0.958359  1.000000  0.858546   \n",
       "growth      0.959038  0.835477    0.818280  0.864222  0.858546  1.000000   \n",
       "momentum    0.928705  0.796420    0.819585  0.818796  0.825563  0.952956   \n",
       "\n",
       "            momentum  \n",
       "market      0.928705  \n",
       "size        0.796420  \n",
       "volatility  0.819585  \n",
       "value       0.818796  \n",
       "risk        0.825563  \n",
       "growth      0.952956  \n",
       "momentum    1.000000  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "retsf.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 110,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.set_printoptions(formatter={'float': lambda x: f'{x:5.2f}'})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "AAPL.O\n",
      "==========================================================================\n",
      "fl: [ 2.30  2.80 -0.70 -1.40 -4.20  2.00 -0.20] | apt: 0.115 | real: 0.301\n",
      "\n",
      "MSFT.O\n",
      "==========================================================================\n",
      "fl: [ 1.50  0.00  0.10 -1.30 -1.40  0.80  1.00] | apt: 0.181 | real: 0.304\n",
      "\n",
      "INTC.O\n",
      "==========================================================================\n",
      "fl: [-3.10  1.60  0.40  1.30 -2.60  2.50  1.10] | apt: 0.186 | real: 0.118\n",
      "\n",
      "AMZN.O\n",
      "==========================================================================\n",
      "fl: [ 9.10  3.30 -1.00 -7.10 -3.10 -1.80  1.20] | apt: 0.019 | real: 0.050\n"
     ]
    }
   ],
   "source": [
    "split = int(len(retsf) * 0.5)\n",
    "for sym in rets.columns[:4]:\n",
    "    print('\\n' + sym)\n",
    "    print(74 * '=')\n",
    "    retsf_, retsd_ = retsf.iloc[:split], retsd.iloc[:split]\n",
    "    reg = np.linalg.lstsq(retsf_, retsd_[sym], rcond=-1)[0]   \n",
    "    retsf_, retsd_ = retsf.iloc[split:], retsd.iloc[split:]\n",
    "    mu_apt = np.dot(retsf_.mean() * 252, reg)\n",
    "    mu_real =  retsd_[sym].mean() * 252\n",
    "    res = res.append(pd.DataFrame({'mu_apt': mu_apt,\n",
    "                    'mu_real': mu_real}, index=[sym,]),\n",
    "                    sort=True)\n",
    "    print('fl: {} | apt: {:.3f} | real: {:.3f}'\n",
    "          .format(reg.round(1), mu_apt, mu_real))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "res.plot(kind='bar', figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 114,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'AMZN.O'"
      ]
     },
     "execution_count": 114,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets_sym = np.dot(retsf_, reg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets_sym = pd.DataFrame(rets_sym,\n",
    "                        columns=[sym + '_apt'],\n",
    "                        index=retsf_.index)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets_sym[sym + '_real'] = retsd_[sym]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 118,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AMZN.O_apt     0.019401\n",
       "AMZN.O_real    0.050344\n",
       "dtype: float64"
      ]
     },
     "execution_count": 118,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets_sym.mean() * 252"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AMZN.O_apt     0.270995\n",
       "AMZN.O_real    0.307653\n",
       "dtype: float64"
      ]
     },
     "execution_count": 119,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets_sym.std() * 252 ** 0.5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 120,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>AMZN.O_apt</th>\n",
       "      <th>AMZN.O_real</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AMZN.O_apt</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.832218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AMZN.O_real</th>\n",
       "      <td>0.832218</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             AMZN.O_apt  AMZN.O_real\n",
       "AMZN.O_apt     1.000000     0.832218\n",
       "AMZN.O_real    0.832218     1.000000"
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets_sym.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rets_sym.cumsum().apply(np.exp).plot(figsize=(10, 6));"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "rets_sym['same'] = (np.sign(rets_sym[sym + '_apt']) ==\n",
    "                    np.sign(rets_sym[sym + '_real']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     288\n",
       "False     89\n",
       "Name: same, dtype: int64"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets_sym['same'].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.7639257294429708"
      ]
     },
     "execution_count": 124,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rets_sym['same'].value_counts()[True] / len(rets_sym)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src='http://hilpisch.com/taim_logo.png' width=\"350px\" align=\"right\">\n",
    "\n",
    "<br><br><br><a href=\"http://tpq.io\" target=\"_blank\">http://tpq.io</a> | <a href=\"http://twitter.com/dyjh\" target=\"_blank\">@dyjh</a> | <a href=\"mailto:ai@tpq.io\">ai@tpq.io</a>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
